과제정보
This research was supported by the Ministry of Food and Drug Safety of the Republic of Korea (21163수입안516).
참고문헌
- Korea Creative Content Agency, "The 2020 Survey on the Korean e-Sports Industry", Korea Creative Content Agency, 2020.
- Sae-Sook Oh and Dae-Hoon Kim, "Analysis of the Academic Research Trend of e-sports", Journal of Wellness, vol. 7, No. 2, pp.113-121, 2012.
- Jung Hwan Cho, "Utilization and Prospect of Sport Big Data", Korean Society For Measurement And Evaluation In Physical Education And Sports Science, vol. 14, No. 3, pp.01-11, 2012.
- Yong Goo Kang and Huy Kang Kim, "Game Bot Detection Based on Action Time Interval", Journal of The Korea Institute of Information Security and Cryptology, vol. 28, No. 5, pp.1153-1160, 2018. https://doi.org/10.13089/JKIISC.2018.28.5.1153
- GGtics, "Analytics/AI to help players win - YOUR.GG", accessed Apr 13, 2021, https://your.gg/?lang=en.
- OP.GG, "LoL Stats, Record Replay, Database, Guide - OP.GG", accessed Apr 13, 2021, https://www.op.gg.
- 일요서울, "사교육 시장에 등장한 '게임학원', 그 배경은?", accessed Apr 13, 2021, http://www.ilyoseoul.co.kr/news/articleView.html?idxno=237470.
- Alexander Neumann, "Developing a Model to Predict Match Outcomes in League of Legends," Barrett, The Honors College Thesis, Arizona State University, 2015.
- Cheolgi Kim and Soowon Lee, "Predicting Win-Loss of League of Legends Using Bidirectional LSTM Embedding", Korea Information Processing Society, vol. 9, No. 2, pp.61-68, 2020.
- Dong-Wook Kim, Jeawon Park and Jaehyun Choi, "A study for the prediction of winning of e-Sports using machine Learning", Jounal of The Korea Society of Information Technology Policy & Management, vol. 9, No. 1, pp.319-325, 2017.
- Jimin Ku and Jaehee Kim, "Development of game indicators and winning forecasting models with game data", Journal of the Korean Data and Information Science Society, vol. 28, no. 2, pp.237-250, 2017. https://doi.org/10.7465/jkdi.2017.28.2.237
- Min-ji Oh, Eun-seon Choi, Som Akhamixay Oui and Wan-sup Cho, "Predicting win-loss using game data and deriving the importance of subdivided variables", The Korea Journal of BigData, vol. 5, No. 2, pp.231-240, 2020. https://doi.org/10.36498/KBIGDT.2020.5.2.231
- Ani, R., Harikumar, V., Devan, A. K., and Deepa, O. S., "Victory prediction in League of Legends using Feature Selection and Ensemble methods", In 2019 International Conference on Intelligent Computing and Control Systems, pp. 74-77, 2018.
- Thompson JJ, Blair MR, Chen L and Henrey AJ, "Video Game Telemetry as a Critical Tool in the Study of Complex Skill Learning", PLoS ONE 8(9): e75129. https://doi.org/10.1371/journal.pone.0075129
- Lee, Sang-Kwang, Seung-Jin Hong, and Seong-Il Yang. "Predicting Game Outcome in Multiplayer Online Battle Arena Games", International Conference on Information and Communication Technology Convergence, IEEE, 2019.
- Riot Games, "Riot Developer Portal", accesse d Apr 13, 2021, https://developer.riotgames.com.
- Gregorutti B., Michel B. and Saint-Pierre P, "Correlation and variable importance in random forests", Statistics and Computing, vol. 27, pp.659-678, 2017. https://doi.org/10.1007/s11222-016-9646-1
- Bzdok, D., Altman, N., and Krzywinski, M., "Statistics versus machine learning", Nature methods, 15(4), pp 233-234, 2018. https://doi.org/10.1038/nmeth.4642
- Rich Caruana and Alexandru Niculescu-Mizil, "An empirical comparison of supervised learning algorithms", In Proceedings of the 23rd international conference on Machine learning, pp.161-168, 2006.
- Bentejac C., Csorgo, A. and Martinez-Munoz G., "A comparative analysis of gradient boosting algorithms", Artificial Intelligence Review, vol. 54, pp.1937-1967, 2021. https://doi.org/10.1007/s10462-020-09896-5
- Van Saeys, Inaki Inza and Pedro Larranaga, "A review of feature selection techniques in bioinformatics", Bioinformatics, Volume 23, Issue 19, pp. 2507-2517, 2007. https://doi.org/10.1093/bioinformatics/btm344
- Nicodemus K.K., "Letter to the Editor: On the stability and ranking of predictors from random forest variable importance measures", Brief Bioinform, vol. 12, No. 4, pp.369-373, 2011. https://doi.org/10.1093/bib/bbr016
- Silva, A., G. Pappa and L. Chaimowicz, "Continuous Outcome Prediction of League of Legends Competitive Matches Using Recurrent Neural Networks.", In Proceedings of SBGames, code: 188226, 2018.
- Ellis Cashmore. "Making Sense of Sports", Routledge, 2010.
-
Seong-Eun Seo and Chi-Yo Kim, "Recognition of the Type and Cause of
Trolling", Korea Game Society, vol. 15, No. 4, pp. 93-110, 2015. https://doi.org/10.7583/JKGS.2015.15.4.93 - Kyu Bok Lee and Young Jae Kim, "Analysis of Factors that Influence Users' Preference for MOBA Game Genre: Focusing on the Game Systems of League of Legends", Global Cultural Contents, vol. 47, pp. 107-124, 2021.